COMputational Models FOR patienT stratification in urologic cancers – Creating robust and trustworthy multimodal AI for health care

Informazioni relative al progetto

COMFORT

ID dell’accordo di sovvenzione: 101079894

DOI

10.3030/101079894

Data della firma CE 17 Marzo 2023

Data di avvio 1 Aprile 2023

Data di completamento 31 Marzo 2027

Finanziato da

• Health

Costo totale

€ 5 906 596,25

Contributo UE

€ 5 906 596,25

Coordinato da

KLINIKUM DER TECHNISCHEN UNIVERSITÄT MÜNCHEN (TUM KLINIKUM)
Germany

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Websites, patent fillings, videos etc. (1)

COMFORT website

Website will inform the public about COMFORT’s aims, progress, & results and will be continuously updated.

Documents, reports (1)

Report on ethical factors and impacts

Report about trustworthiness analysis (i.e., transparency, bias-free, privacy concern) of the developed AI modes.

Pubblicazioni

Peer reviewed articles (3)

Robust Renal Mass Segmentation on CT: A Validation Study of an AI-Based Framework

Autori: Sarah de Boer, Hartmut Häntze, Kiran Vaidhya Venkadesh, Myrthe A. D. Buser, Gabriel E. Humpire Mamani, Lina Xu, Lisa C. Adams, Jawed Nawabi, Keno K. Bressem, Bram van Ginneken, Mathias Prokop, Alessa Hering
Pubblicato in: Machine Learning for Biomedical Imaging, Numero 2026, 2026, ISSN 2766-905X
Editore: Machine Learning for Biomedical Imaging
DOI: 10.59275/J.MELBA.2026-67G5

Global cross-sectional student survey on AI in medical, dental, and veterinary education and practice at 192 faculties

Autori: Felix Busch, Lena Hoffmann, Daniel Truhn, Esteban Ortiz-Prado, Marcus R. Makowski, Keno K. Bressem, Lisa C. Adams & COMFORT Consortium
Pubblicato in: BMC Medical Education, 2024, ISSN 1472-6920
Editore: Springer
DOI: 10.1186/S12909-024-06035-4

Segmenting Whole-Body MRI and CT for Multiorgan Anatomic Structure Delineation

Autori: Hartmut Häntze
Pubblicato in: Radiology Artificial Intelligence, ISSN 2638-6100
Editore: Radiological Society of North America
DOI: 10.1148/RYAI.240777

Conference proceedings (4)

Assessing the Fragility of SHAP-Based Model Explanations Using Counterfactuals

Autori: Lili Jiang
Editore: PMLR (Proceedings of Machine Learning Research)

Patient Attitudes Worldwide Towards AI in Healthcare and Diagnostics: Results from the COMFORT Study

Autori: Keno Bressem
Pubblicato in: ISSN 2574-3805
Editore: American Medical Association
DOI: 10.1001/JAMANETWORKOPEN.2025.14452

Revisiting Clinical Outcome Prediction for MIMIC-IV

Autori: Tom Röhr, Alexei Figueroa, Jens-Michalis Papaioannou, Conor Fallon, Keno Bressem, Wolfgang Nejdl, Alexander Löser
Pubblicato in: Proceedings of the 6th Clinical Natural Language Processing Workshop, 2024
Editore: Association for Computational Linguistics
DOI: 10.18653/v1/2024.clinicalnlp-1.18

"""Where does it hurt?"" - Dataset and Study on Physician Intent Trajectories in Doctor Patient Dialogues"

Autori: Dennis Fast
Pubblicato in: ECAI, ISSN 1879-8314
Editore: IOS Press

Book chapters (1)

Deformable MRI Sequence Registration for AI-Based Prostate Cancer Diagnosis

Autori: Alessa Hering, Sarah de Boer, Anindo Saha, Jasper J. Twilt, Mattias P. Heinrich, Derya Yakar, Maarten de Rooij, Henkjan Huisman, Joeran S. Bosma
Pubblicato in: Lecture Notes in Computer Science, Biomedical Image Registration, 2024
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-73480-9_12